Journal articles: 'Coordinate registration'

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Michael, G. G. "Coordinate registration by automated crater recognition." Planetary and Space Science 51, no. 9-10 (August 2003): 563–68. http://dx.doi.org/10.1016/s0032-0633(03)00074-6.

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Nouri, Mahtab, Arash Farzan, Ali Reza Akbarzadeh Baghban, and Reza Massudi. "Comparison of clinical bracket point registration with 3D laser scanner and coordinate measuring machine." Dental Press Journal of Orthodontics 20, no. 1 (February 2015): 59–65. http://dx.doi.org/10.1590/2176-9451.20.1.059-065.oar.

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OBJECTIVE: The aim of the present study was to assess the diagnostic value of a laser scanner developed to determine the coordinates of clinical bracket points and to compare with the results of a coordinate measuring machine (CMM). METHODS: This diagnostic experimental study was conducted on maxillary and mandibular orthodontic study casts of 18 adults with normal Class I occlusion. First, the coordinates of the bracket points were measured on all casts by a CMM. Then, the three-dimensional coordinates (X, Y, Z) of the bracket points were measured on the same casts by a 3D laser scanner designed at Shahid Beheshti University, Tehran, Iran. The validity and reliability of each system were assessed by means of intraclass correlation coefficient (ICC) and Dahlberg's formula. RESULTS: The difference between the mean dimension and the actual value for the CMM was 0.0066 mm. (95% CI: 69.98340, 69.99140). The mean difference for the laser scanner was 0.107 ± 0.133 mm (95% CI: -0.002, 0.24). In each method, differences were not significant. The ICC comparing the two methods was 0.998 for the X coordinate, and 0.996 for the Y coordinate; the mean difference for coordinates recorded in the entire arch and for each tooth was 0.616 mm. CONCLUSION: The accuracy of clinical bracket point coordinates measured by the laser scanner was equal to that of CMM. The mean difference in measurements was within the range of operator errors.

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Pulford, G. W. "OTHR multipath tracking with uncertain coordinate registration." IEEE Transactions on Aerospace and Electronic Systems 40, no. 1 (January 2004): 38–56. http://dx.doi.org/10.1109/taes.2004.1292141.

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Schicho, Kurt, Michael Figl, Rudolf Seemann, Markus Donat, Michael L. Pretterklieber, Wolfgang Birkfellner, Astrid Reichwein, et al. "Comparison of laser surface scanning and fiducial marker–based registration in frameless stereotaxy." Journal of Neurosurgery 106, no. 4 (April 2007): 704–9. http://dx.doi.org/10.3171/jns.2007.106.4.704.

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✓The authors compared the accuracy of laser surface scanning patient registration using the commercially available Fazer (Medtronic, Inc.) with the conventional registration procedure based on fiducial markers (FMs) in computer-assisted surgery. Four anatomical head specimens were prepared with 10 titanium microscrews placed at defined locations and scanned with a 16-slice spiral computed tomography unit. To compare the two registration methods, each method was applied five times for each cadaveric specimen; thus data were obtained from 40 registrations. Five microscrews (selected following a randomization protocol) were used for each FM-based registration; the other five FMs were selected for coordinate measurements by touching with a point measurement stylus. Coordinates of these points were also measured manually on the screen of the navigation computer. Coordinates were measured in the same manner after laser surface registration. The root mean square error as calculated by the navigation system ranged from 1.3 to 3.2 mm (mean 1.8 mm) with the Fazer and from 0.3 to 1.8 mm (mean 1.0 mm) with FM-based registration. The overall mean deviations (the arithmetic mean of the mean deviations of measurements on the four specimens) were 3.0 mm (standard deviation [SD] range 1.4–2.6 mm) with the Fazer and 1.4 mm (SD range 0.4–0.9 mm) with the FMs. The Fazer registration scans 300 surface points. Statistical tests showed the difference in the accuracy of these methods to be highly significant. In accordance with the findings of other groups, the authors concluded that the inclusion of a larger number of registration points might improve the accuracy of Fazer registration.

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Pan, Meisen, Jianjun Jiang, Fen Zhang, and Qiusheng Rong. "MEDICAL IMAGE REGISTRATION BASED ON IMPROVED FUZZY C-MEANS CLUSTERING." Biomedical Engineering: Applications, Basis and Communications 27, no. 04 (August 2015): 1550032. http://dx.doi.org/10.4015/s1016237215500325.

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The mutual information (MI) technology and the iterative closest point (ICP) algorithm, as intensity-based and feature-based image registration methods respectively, are commonly put into use in medical image registration. But some naturally existing things which restrict the further development need to be faced and be solved. On one hand, they remain heavy calculation costs and low registration efficiencies. On the other hand, since they seriously depend on whether the initial rotation and translation registration parameters can be exactly selected, they often trap in the local optima and even fail to register images. In this paper, we compute the centroids of the reference and floating images by using the image moments to obtain the initial translation values, and use improved fuzzy C-means clustering (IFCM) to classify the image coordinates. Before clustering, this proposed method first centralizes the medical image coordinates, creates the two-row coordinate matrix to construct the two-dimensional (2D) sample set partitioned into two classes, and computes the slope of a straight line fitted to the two classes, finally derives the rotation angle from solving the arc tangent of the slope and obtains the initial rotation values. The experimental results show that, this proposed method has a fairly simple implementation, a low computational load, a fast registration and good registration accuracy. Also, it can efficiently avoid trapping in the local optima and meets both mono-modality and multi-modality image registrations.

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IUKHNO, Alona, Dmytro SOPOV, and Dmytro HOPTSII. "PERFORMANCE OF ENGINEERING SURVEYS AS AN INTEGRAL PART OF LAND AND CADASTRE WORKS IN PREPARATION OF LAND PLOTS FOR REGISTRATION IN THE BASE OF THE STATE LAND CADASTER." Ukrainian Journal of Applied Economics 6, no. 3 (September 2, 2021): 273–80. http://dx.doi.org/10.36887/2415-8453-2021-3-37.

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Performing engineering surveys is a mandatory part of the development of technical documentation on land management. Surveys allow to confirm the accuracy of the performed geodetic or topographic survey. In particular, the accuracy of determining the geodetic coordinates of the turning points of the boundaries of the land, to link the turning points of the boundaries of the land to the geodetic points of the State Geodetic Network of Ukraine. The main purpose of the article is to reflect the main components of engineering surveys as part of land cadastral works in preparation of land for registration in the database of the State Land Cadastre. The coordinate basis for land management is the State Geodetic Reference Coordinate System USK-2000, the geodetic basis for land management – points of the State Geodetic Network 1-3 classes, points of geodetic networks of compaction 4 class, 1 and 2 categories, points of the surveying network. The coordinates of the points of the State Geodetic Network of Ukraine, geodetic networks of condensing and turning points of the boundaries of geospatial objects are determined by rectangular coordinates (x, y) in the Gauss-Krueger projection in the USC-2000 coordinate system or local coordinate systems. related to the USC-2000 coordinate system. The control of the differential field of coordinate corrections when working with the use of RTK technologies is carried out at least at the two nearest points of DGM and GMZ, the coordinates of which are obtained from the administrator of the geodetic data bank. The difference in the values of the coordinates of control points should not exceed 0.1 m in cities of regional importance, 0.2 m - in other cities and towns, 0.3 m - in rural areas and 0.5 m - outside the settlements. Keywords: engineering surveys, State Geodetic Network of Ukraine, land cadastral works, coordinate system, State Land Cadastre.

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Zhu, Jiang, Yuichi Takekuma, Tomohisa Tanaka, and Yoshio Saito. "3D Model Registration Based on Feature Extraction." Advanced Materials Research 299-300 (July 2011): 1091–94. http://dx.doi.org/10.4028/www.scientific.net/amr.299-300.1091.

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Currently, design and processing of complicated model are enabled by the progress of the CAD/CAM system. In shape measurement, high precision measurement is performed using CMM. In order to evaluate the machined part, the designed model made by CAD system the point cloud data provided by the measurement system are analyzed and compared. Usually, the designed CAD model and measured point cloud data are made in the different coordinate systems, it is necessary to register those models in the same coordinate system for evaluation. In this research, a 3D model registration method based on feature extraction and iterative closest point (ICP) algorithm is proposed. It could efficiently and accurately register two models in different coordinate systems, and effectively avoid the problem of localized solution.

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Min, Kong, Wang Guohong, and Wang Yongcheng. "Coordinate registration algorithms for over-the-horizon radar." Journal of Systems Engineering and Electronics 17, no. 4 (December 2006): 725–30. http://dx.doi.org/10.1016/s1004-4132(07)60006-1.

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Ye, Tie Li, Xue Yi Li, and Qing Liang Zeng. "Measuring Data Registration Based on Triangle Constraint." Applied Mechanics and Materials 271-272 (December 2012): 1346–50. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.1346.

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This paper studied the fine registration techniques of measuring data of complex product and proposed a new registration method based on triangle constraint. Firstly, the paper made a research on specifying the proper measuring reference points and the setting of reference coordinate system, and afterwards proposed a fine registration algorithm of measuring data, Which is about realizing the fusion of reference coordinate system based on the congruent judgment of reference triangle and fulfilling precise match of data with measuring error on the basis of controlling the rotation of data blocks and minimizing the registration error.

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Tucker, Thomas M., and Thomas R. Kurfess. "Point Cloud to CAD Model Registration Methods in Manufacturing Inspection." Journal of Computing and Information Science in Engineering 6, no. 4 (July 27, 2006): 418–21. http://dx.doi.org/10.1115/1.2353852.

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Modern computer vision and coordinate metrology systems provide an ever-increasing flow of information from the physical world we live in to the virtual world inside computer systems. Often the coordinate system of the metrology device has a different coordinate frame from that of the existing objects in the virtual world. To rectify these differences, a process called registration is often applied. This paper uses a case study to highlight the differences between various registration techniques.

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Knisely, Jonathan P., James E. Bond, Ning J. Yue, Colin Studholme, and Alain C. J. de Lotbinière. "Image registration and calculation of a biologically effective dose for multisession radiosurgical treatments." Journal of Neurosurgery 93, supplement_3 (December 2000): 208–18. http://dx.doi.org/10.3171/jns.2000.93.supplement_3.0208.

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✓ The purpose of this study was to develop techniques for registering image sets associated with staged or multifraction radiosurgical treatments of large targets with the Leksell gamma knife to transform shot coordinates between treatment sessions and produce cumulative dose distributions and to investigate the theoretical biological effects of such protracted treatments by means of such concepts as the linear—quadratic model and biologically effective dose. An image registration technique based on normalized mutual information was adapted to produce one fused-image study from an imaging series acquired during distinct treatment sessions. A spreadsheet computer program was developed to determine coordinate transformations between the associated stereotactic coordinate systems based on digitized coordinates of fiducial markers appearing on the fused images. Coordinates of shots used during one treatment session could then be transformed to the stereotactic space of another session, and cumulative dose distributions could be computed. The procedure was applied to the two-stage treatment of a giant arteriovenous malformation (AVM). Overall uncertainty in each transformed shot position is approximately 0.7 mm. An effective single-fraction dose (Deff) was defined and computed for the two-stage AVM treatment. The simple summed dose distribution was compared with the Deff distribution. Because dose values differ significantly in overlap regions between the individual distributions, the clinical usefulness of the simple cumulative distribution is dubious. It may be useful for a future update of the GammaPlan treatment planning software to generate effective single-session dose distributions for such cases.

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Krolik, J. L., and R. H. Anderson. "Maximum likelihood coordinate registration for over-the-horizon radar." IEEE Transactions on Signal Processing 45, no. 4 (April 1997): 945–59. http://dx.doi.org/10.1109/78.564183.

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Noble, Nicholas M. I., Derek L. G. Hill, Marcel Breeuwer, Julia A. Schnabel, David J. Hawkes, Frans A. Gerritsen, and Reza Razavi. "Myocardial delineation via registration in a polar coordinate system1." Academic Radiology 10, no. 12 (December 2003): 1349–58. http://dx.doi.org/10.1016/s1076-6332(03)00537-3.

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Zhao, Haibin, Nabil Anwer, and Pierre Bourdet. "Curvature-based Registration and Segmentation for Multisensor Coordinate Metrology." Procedia CIRP 10 (2013): 112–18. http://dx.doi.org/10.1016/j.procir.2013.08.020.

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Shaw, L., and A. Weckenmann. "Automatic registration method for hybrid optical coordinate measuring technology." CIRP Annals 60, no. 1 (2011): 539–42. http://dx.doi.org/10.1016/j.cirp.2011.03.055.

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Deng, Zhengping, Shuanggao Li, and Xiang Huang. "Uncertainties evaluation of coordinate transformation parameters in the large-scale measurement for aircraft assembly." Sensor Review 38, no. 4 (September 17, 2018): 542–50. http://dx.doi.org/10.1108/sr-08-2017-0150.

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Purpose For the measurement of large-scale components in aircraft assembly, the evaluation of coordinate transformation parameters between the coordinate frames of individual measurement systems to the assembly frame is an essential task, which is usually completed by registration of the enhanced reference system (ERS) points. This paper aims to propose an analytical method to evaluate the uncertainties of transformation parameters considering both the measurement error and the deployment error of ERS points. Design/methodology/approach For each measuring station, the measured coordinates of ERS points are first roughly registered to the assembly coordinate system using the singular value decomposition method. Then, a linear transformation model considering the measurement error and deployment error of ERS points is developed, and the analytical solution of transformation parameters’ uncertainties is derived. Moreover, the covariance matrix of each ERS points in the transformation evaluation is calculated based on a new uncertainty ellipsoid model and variance-covariance propagation law. Findings For the transformation of both single and multiple measuring stations, the derived uncertainties of transformation parameters by the proposed analytical method are identical to that obtained by the state-of-the-art iterative method, but the solution process is simpler, and the computation expenses are much less. Originality/value The proposed uncertainty evaluation method would be useful for in-site measurement and optimization of the configuration of ERS points in the design of fixture and large assembly field. It could also be applied to other registration applications with errors on both sides of registration points.

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Yuan, Jianying, Qiong Wang, Xiaoliang Jiang, and Bailin Li. "A High-Precision Registration Technology Based on Bundle Adjustment in Structured Light Scanning System." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/897347.

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The multiview 3D data registration precision will decrease with the increasing number of registrations when measuring a large scale object using structured light scanning. In this paper, we propose a high-precision registration method based on multiple view geometry theory in order to solve this problem. First, a multiview network is constructed during the scanning process. The bundle adjustment method from digital close range photogrammetry is used to optimize the multiview network to obtain high-precision global control points. After that, the 3D data under each local coordinate of each scan are registered with the global control points. The method overcomes the error accumulation in the traditional registration process and reduces the time consumption of the following 3D data global optimization. The multiview 3D scan registration precision and efficiency are increased. Experiments verify the effectiveness of the proposed algorithm.

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You, Bo, Hongyu Chen, Jiayu Li, Changfeng Li, and Hui Chen. "Fast Point Cloud Registration Algorithm Based on 3DNPFH Descriptor." Photonics 9, no. 6 (June 15, 2022): 414. http://dx.doi.org/10.3390/photonics9060414.

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Although researchers have investigated a variety of approaches to the development of three-dimensional (3D) point cloud matching algorithms, the results have been limited by low accuracy and slow speed when registering large numbers of point cloud data. To address this problem, a new fast point cloud registration algorithm based on a 3D neighborhood point feature histogram (3DNPFH) descriptor is proposed for fast point cloud registration. With a 3DNPFH, the 3D key-point locations are first transformed into a new 3D coordinate system, and the key points generated from similar 3D surfaces are then close to each other in the newly generated space. Subsequently, a neighborhood point feature histogram (NPFH) was designed to encode neighborhood information by combining the normal vectors, curvature, and distance features of a point cloud, thus forming a 3DNPFH (3D + NPFH). The descriptor searches radially for 3D key point locations in the new 3D coordinate system, reducing the search coordinate system for the corresponding point pairs. The “NPFH” descriptor is then coarsely aligned using the random sample consensus (RANSAC) algorithm. Experiment results show that the algorithm is fast and maintains high alignment accuracy on several popular benchmark datasets, as well as our own data.

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Guo, Zhen, Zengfu Wang, Yuhang Hao, Hua Lan, and Quan Pan. "An Improved Coordinate Registration for Over-the-Horizon Radar Using Reference Sources." Electronics 10, no. 24 (December 11, 2021): 3086. http://dx.doi.org/10.3390/electronics10243086.

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In the target localization of skywave over-the-horizon radar (OTHR), the error of the ionospheric parameters is one main error source. To reduce the error of ionospheric parameters, a method using both the information of reference sources (e.g., terrain features, ADS-B) in ground coordinates and the corresponding OTHR measurements is proposed to estimate the ionospheric parameters. Describing the ionospheric electron density profile by the quasi-parabolic model, the estimation of the ionospheric parameters is formulated as an inverse problem, and is solved by a Markov chain Monte Carlo method due to the complicated ray path equations. Simulation results show that, comparing with using the a prior value of the ionospheric parameters, using the estimated ionospheric parameters based on four airliners in OTHR coordinate registration process, the ground range RMSE of interested targets is reduced from 2.86 to 1.13 km and the corresponding improvement ratio is up to 60.39%. This illustrates that the proposed method using reference sources is able to significantly improve the accuracy of target localization.

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Tian, Heqiang, Peng Yang, Chunjian Su, and Zhiqiang Dong. "ICP Registration Technology based on the Coordinate System Direction Fit." International Journal of Security and Its Applications 9, no. 12 (December 31, 2015): 47–56. http://dx.doi.org/10.14257/ijsia.2015.9.12.06.

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Pfeifer, Tilo, Benjamin Montavon, Martin Peterek, and Ben Hughes. "Artifact-free coordinate registration of heterogeneous Large-Scale Metrology systems." CIRP Annals 68, no. 1 (2019): 503–6. http://dx.doi.org/10.1016/j.cirp.2019.04.077.

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Choi, Yoo Joo, Min Jeong Kim, Ji Young Park, Joo Young Park, Hyun Joo Yun, Seung Bong Hong, and Myoung Hee Kim. "Surface Curvature-Based MR-PET Image Registration and Hybrid Hippocampus Modeling." Key Engineering Materials 277-279 (January 2005): 212–18. http://dx.doi.org/10.4028/www.scientific.net/kem.277-279.212.

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The correlations between the anatomical shape of brain subsystems and brain diseases have been widely researched in order to diagnose and prevent the diseases. In order to study the anatomical and the metabolic correlations, a correct image registration between the anatomical image and the metabolic image is required. In this study, we present a multi-modality image registration based on surface distance and curvature information. The proposed scheme enhances the stability and accuracy of registration results. In the first step, we extract the surface voxels and object-centered coordinate systems from reference and test volume data sets, respectively. In order to guarantee a stable registration result that is independent of the initial position or direction of the test object, two object-centered coordinate systems are overlapped before the fine registration process. In the fine registration step, we minimize the cost function to be defined by the surface distance and surface curvature difference between reference and test objects. The proposed cost function enhanced registration accuracy, which was verified through the registration error ratio and 2D/3D visual inspection of the registration results. Furthermore, we suggest a reconstruction of a hybrid hippocampus model that includes anatomical and functional information using a multi-modality image registration result.

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Li Siyuan, 李思远, 刘瑾 Liu Jin, 杨海马 Yang Haima, and 刘海珊 Liu Haishan. "分两阶段变换坐标的点云粗配准算法." Laser & Optoelectronics Progress 59, no. 16 (2022): 1610005. http://dx.doi.org/10.3788/lop202259.1610005.

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Bond, Jason, and William Robertson. "The Evolution of Nova Scotia's Coordinate Referencing Systems." GEOMATICA 69, no. 4 (December 2015): 407–18. http://dx.doi.org/10.5623/cig2015-403.

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Despite its rich history, the evolution of the coordinate referencing system in Nova Scotia has not been well documented. As the foundation for the property boundary fabric and land registration system for the province, it is critical that this knowledge is maintained. It is the key to being able to link surveys of the past with the pres ent. This research strives to capture important coordinate referencing knowledge from those that have worked with the system and have since retired from the Nova Scotia provincial government or former Land Registration and Information Service. A detailed review of documentation discussing various historical aspects of coordinate referencing in Nova Scotia was conducted. Personnel involved with the implementation of the systems were interviewed to pro vide first-hand accounts of operational details. This information is captured and is presented chronologically. An outlook on the future of the coordinate referencing program is also discussed.

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Yue, Rui, Hao Xu, Jianqing Wu, Renjuan Sun, and Changwei Yuan. "Data Registration with Ground Points for Roadside LiDAR Sensors." Remote Sensing 11, no. 11 (June 5, 2019): 1354. http://dx.doi.org/10.3390/rs11111354.

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The Light Detection and Ranging (LiDAR) sensors are being considered as new traffic infrastructure sensors to detect road users’ trajectories for connected/autonomous vehicles and other traffic engineering applications. A LiDAR-enhanced traffic infrastructure system requires multiple LiDAR sensors around intersections, along with road segments, which can provide a seamless detection range at intersections or along arterials. Each LiDAR sensor generates cloud points of surrounding objects in a local coordinate system with the sensor at the origin, so it is necessary to integrate multiple roadside LiDAR sensors’ data into the same coordinate system. None of existing methods can integrate the data from roadside LiDAR sensors, because the extensive detection range of roadside sensors generates low-density cloud points and the alignment of roadside sensors is different from mapping scans or autonomous sensing systems. This paper presents a method to register datasets from multiple roadside LiDAR sensors. This approach innovatively integrates LiDAR datasets with 3D cloud points of road surface and 2D reference point features, so the method is abbreviated as RGP (Registration with Ground and Points). The RGP method applies optimization algorithms to identify the optimized linear coordinate transformation. This research considered the genetic algorithm (global optimization) and the hill climbing algorithm (local optimization). The performance of the RGP method and the different optimization algorithms was evaluated with field LiDAR sensors data. When the developed process can integrate data from roadside sensors, it can also register LiDAR sensors’ data on an autonomous vehicle or a robot.

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Yang, Hui Jun, Dong Jian He, and Peng He. "Optimal Transformation in Fruit Scans Registration." Applied Mechanics and Materials 229-231 (November 2012): 1746–50. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1746.

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Transformation used for aligning feature-based scans pair, is pivotal in optimization and simplification for splat-based scans. In this paper, a novel optimal transformation algorithm is first presented by take advantage of transformation between two coordinate system which is directly determined by position and normal. And then transformation is simplified by eliminating the redundant transformation to remit the computation complexity. At last, we give the transformation result of apple scans registration in our experiment platform and verify the accuracy and performance in fast computation of algorithm.

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Khang, Seungwoo, Taeyong Park, Junwoo Lee, Kyung Won Kim, Hyunjoo Song, and Jeongjin Lee. "Computer-Aided Breast Surgery Framework Using a Markerless Augmented Reality Method." Diagnostics 12, no. 12 (December 11, 2022): 3123. http://dx.doi.org/10.3390/diagnostics12123123.

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This study proposes a markerless Augmented Reality (AR) surgical framework for breast lesion removal using a depth sensor and 3D breast Computed Tomography (CT) images. A patient mesh in the real coordinate system is acquired through a patient 3D scan using a depth sensor for registration. The patient mesh on the virtual coordinate system is obtained by contrast-based skin segmentation in 3D mesh generated from breast CT scans. Then, the nipple area is detected based on the gradient in the segmented skin area. The region of interest (ROI) is set based on the detection result to select the vertices in the virtual coordinate system. The mesh on the real and virtual coordinate systems is first aligned by matching the center of mass, and the Iterative Closest Point (ICP) method is applied to perform more precise registration. Experimental results of 20 patients’ data showed 98.35 ± 0.71% skin segmentation accuracy in terms of Dice Similarity Coefficient (DSC) value, 2.79 ± 1.54 mm nipple detection error, and 4.69 ± 1.95 mm registration error. Experiments using phantom and patient data also confirmed high accuracy in AR visualization. The proposed method in this study showed that the 3D AR visualization of medical data on the patient’s body is possible by using a single depth sensor without having to use markers.

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Koguciuk, Daniel. "Parallel RANSAC for Point Cloud Registration." Foundations of Computing and Decision Sciences 42, no. 3 (September 1, 2017): 203–17. http://dx.doi.org/10.1515/fcds-2017-0010.

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AbstractIn this paper, a project and implementation of the parallel RANSAC algorithm in CUDA architecture for point cloud registration are presented. At the beginning, a serial state of the art method with several heuristic improvements from the literature compared to basic RANSAC is introduced. Subsequently, its algorithmic parallelization and CUDA implementation details are discussed. The comparative test has proven a significant program execution acceleration. The result is finding of the local coordinate system of the object in the scene in the near real-time conditions. The source code is shared on the Internet as a part of the Heuros system.

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Sharp, G. C., S. W. Lee, and D. K. Wehe. "Multiview registration of 3D scenes by minimizing error between coordinate frames." IEEE Transactions on Pattern Analysis and Machine Intelligence 26, no. 8 (August 2004): 1037–50. http://dx.doi.org/10.1109/tpami.2004.49.

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Sánchez-Beato, Alfonso. "Coordinate-descent super-resolution and registration for parametric global motion models." Journal of Visual Communication and Image Representation 23, no. 7 (October 2012): 1060–67. http://dx.doi.org/10.1016/j.jvcir.2012.07.003.

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Watanabe, Yoichi, and Eunyoung Han. "Image registration accuracy of GammaPlan: a phantom study." Journal of Neurosurgery 109, Supplement (December 2008): 21–24. http://dx.doi.org/10.3171/jns/2008/109/12/s5.

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Object The authors evaluated the accuracy of the automatic image coregistration function implemented in the Leksell GammaPlan treatment planning software (Version 4C with MultiView Extension and Version 8.0). Methods The authors used a phantom with 9 landmarks (tips of thin cylindrical acrylic rods) evenly distributed in the treatment space. Two sets of images of the phantom were taken with both CT and MR imaging systems. The first image was obtained with the phantom aligned with the scanner's axis and the second scan was made by intentionally shifting and rotating the phantom relative to the scanner's axis. The authors attempted image registration of 2 CT image sets, CT and MR image sets, and 2 MR image sets. The accuracy of image registration was evaluated by measuring the x, y, and z coordinate values of the landmarks on each image set after 2 image sets were coregistered. The authors calculated the differences of the x, y, and z values and the distance, d, between corresponding landmarks in 2 image sets. To minimize interobserver dependence of coordinate measurements, 2 physicists did measurements independently. Results The distances, d, averaged over the 9 landmarks, were 2.63 ± 1.64 and 0.95 ± 0.25 mm for CT–CT and MR–MR image registrations, respectively. When the CT images of the air-filled phantom and MR images were coregistered, however, the algorithm performed poorly: d = 13.8 ± 1.23 mm. To remedy this, the authors undertook a 2-step process by first performing landmark-based registration of the 2 image sets and subsequently applying the automatic registration. With this approach, the mean distance drastically improved: d = 0.74 ± 0.31 mm. When the water-filled phantom was used for CT scans, the registration accuracy of CT and MR image sets was acceptable without the 2-step registration process: d = 1.18 ± 0.36 mm. Conclusions The accuracy of automatic registration of image sets from the same modality was within the voxel size of the scanned images. The accuracy of CT–MR image registration strongly depended on whether the phantom for CT scans was filled with air or water. This indicates the significant effect of the amount of common data available for a mutual information-based algorithm on the accuracy.

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Meng, Fan Wen, Lu Shen Wu, and Qing Jin Peng. "Automatic Point Clouds Registration Based on the Method of Least Squares." Key Engineering Materials 419-420 (October 2009): 305–8. http://dx.doi.org/10.4028/www.scientific.net/kem.419-420.305.

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An object has to be measured to recover its 3D shape in reverse engineering applications. The object surface is sampled point by point using a fringe projection. The method of least squares is used to match overlapping surfaces to estimate transformation parameters between a local coordinate system and the template coordinate system. The Gauss–Markoff model can minimize the sum of squares of Euclidean distances between surfaces for matching arbitrarily oriented 3D surface patches. This research uses the least squares method for the registration of point clouds. A relief example shows the feasibility of the proposed method. It takes about 4 seconds for the registration of 1531209 points with the error less than 0.03mm, and the iteration number is only 20. The surface profile is complete and smooth after the registration, which can meet the requirement of surface reconstruction.

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Posada, R., Ch Daul, D. Wolf, and P. Aletti. "Towards a Noninvasive Intracranial Tumor Irradiation Using 3D Optical Imaging and Multimodal Data Registration." International Journal of Biomedical Imaging 2007 (2007): 1–14. http://dx.doi.org/10.1155/2007/62030.

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Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes.

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Watchman, Christopher J., Russell J. Hamilton, Baldassarre Stea, and Alan J. Mignault. "PATIENT POSITIONING USING IMPLANTED GOLD MARKERS WITH THE NOVALIS BODY SYSTEM IN THE THORACIC SPINE." Neurosurgery 62, suppl_5 (May 1, 2008): A62—A68. http://dx.doi.org/10.1227/01.neu.0000325938.08605.eb.

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ABSTRACT OBJECTIVE To evaluate the effectiveness of implanted gold marker registration compared with bony fusion alignment for patient positioning using the Novalis Body system. METHODS Eighteen treatment fractions of stereotactic spinal radiotherapy were analyzed for three patients who each had three implanted gold seeds placed near their spinal lesions before radiotherapy. At each treatment session, the registration was first performed using bony fusion and then verified by another bony fusion, followed by registration with implanted markers. The software reported the calculated shifts for both methods. In addition, the actual three-dimensional coordinate positions of the markers were read using PTDReader software. Implanted marker positions were analyzed for variations in individual maker coordinate displacement, interseed distances, and area transcribed by them. Measured positional differences between the two fusion methods were applied to actual treatment plans to assess the resulting dosimetric differences in the treatment plans. RESULTS Both fusion algorithms were shown to localize the patient well, within 1.5 mm, but the implanted marker fusion consistently related less deviation from the planned isocenter, by approximately 0.5 mm, than did the bony fusion. Exceptions to this localization occurred when the average interseed distances were less than 3.0 cm and resulted in the two registration methods being equivalent. Implanted spine markers were also shown to have less than 0.7 mm deviation from the planned marker coordinates, indicating no migration of the seeds. Dose distributions were found to be highly dependant on differences in fusion method, with spinal cord doses up to 350% greater with bony fusion than with implanted markers. CONCLUSION Implanted markers used with the Novalis Body system have been shown to be more effective in patient positioning than the bony fusion method in the thoracic spine.

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Verma, M. K., and M. Yadav. "REGISTRATION, GEOREFERENCING AND PROCESSING OF MULTIPLE LASER SCANS ACQUIRED BY TERRESTRIAL LASER SCANNER FOR ESTIMATING TREE MORPHOLOGICAL PARAMETERS." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (January 14, 2023): 737–42. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-737-2023.

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Abstract. The trees inventory is very important for forestry and environment-related issues, where tree morphology is one of the key components. LiDAR technology is being selected over other techniques for the trees three-dimensional mapping and inventory. In this paper a methodology for point cloud registration and georeferencing of LiDAR point cloud, and computation of tree morphological parameters, namely tree height, crown diameter, crown projection area is presented. The instruments used for the point cloud acquisition, registration and georeferencing were total station, global navigation satellite system, terrestrial laser scanner. Data from all three instruments were transformed into a common coordinate system that is Universal Transverse Mercator coordinate system. In transformed point cloud, the z-axis of the coordinate system is towards plumb line. The tree height, crown diameter, crown projection area are computed based on point cloud-derived canopy height model and tree top detection.

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MILUȚ, MARIUS, NICOLAE POP, ALIN CROITORU, CLAUDIU BUZATU, and N. UNGUREANU. "USE OF MODERN TECHNIQUE IN PREPARING THE TECHNICAL DOCUMENTATION FOR THE REGISTRATION IN THE LAND BOOK OF A PROPERTY." "Annals of the University of Craiova - Agriculture Montanology Cadastre Series " 51, no. 2 (December 20, 2020): 373–79. http://dx.doi.org/10.52846/aamc.2021.02.45.

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The paper presents the way of drawing up the cadastral documentation for the first registration in the Land Book of a property. The total station and GNSS receivers were used as topographic devices for measurements, which offered a high accuracy of the measured data and a shortening of the time spent in the field. The data processing and the elaboration of the documentation was done through specialized programs (Toposys, Autocad). As the surveying method was used the method of closed planimetric traverse supported on known coordinate points (previously determined with GNSS technology), combined with the method of polar coordinates.

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Sharafutdinova, Anzhelika A., and Michael Ja Bryn. "TECHNIQUE FOR DESIGNING AND CONSTRUCTING A GEODETIC NETWORK WHEN PERFORMING TERRESTRIAL LASER SCANNING AT INDUSTRIAL OBJECT." Vestnik SSUGT (Siberian State University of Geosystems and Technologies) 27, no. 2 (2022): 72–85. http://dx.doi.org/10.33764/2411-1759-2022-27-2-72-85.

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When performing terrestrial laser scanning of large industrial facilities, it must give special atten-tion to designing and establishing a geodetic network to datum transformation measurements into a coordinate system. However, the design of geodetic networks by traditional geodesy methods does not consider all the features of the technique of terrestrial laser scanning. Also worth taking into account is the specifics of laser scanning data processing. Therefore, it is necessary to develop a methodology for designing and establishing a geodetic network in the context of terrestrial laser scanning. For this, the article analyzes the features of terrestrial laser scanning of large industrial facilities and methods for measurement results processing. Based on the analysis and practical experience, developing a flow chart for establishing a geodetic network was on the condition that registration of point cloud perform-ing used iterative closest points algorithm and datum transformation coordinate system performing us-ing HDS targets. Also, based on practical experience, the dependence of the values of the root-mean-square error of registration point cloud and the root-mean-square error of laser scanning station posi-tioning on the distance between the stations. As a result, a methodology for designing and establishing the geodetic network has been substantiated, including two stages. The first stage is the design and ac-curacy assessment of the geodetic control network, the coordinates of which are determined from the datum points by traditional geodesy methods. The second stage is the design and accuracy assessment of the laser scanning station positioning, the coordinates of which are determined from the geodetic control network.

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Barbero-García and Lerma. "Assessment of Registration Methods for Cranial 3D Modelling." Proceedings 19, no. 1 (July 15, 2019): 8. http://dx.doi.org/10.3390/proceedings2019019008.

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Three-dimensional (3D) models are a useful tool for cranial deformation analysis in infants. The registration of the head 3D models to a known coordinate system is vital for the obtainment of parameters and indexes that quantify deformation. In this study, three registration methodologies have been tested based on the principal component analysis (PCA) without tie points, and PCA measuring manually two and three identified tie points. Results show that the approach using PCA plus three manually identified tie points provides enough accuracy for the given application.

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Zadeba, E. A., A. A. Borisov, R. M. Fakhrutdinov, R. P. Kokoulin, K. G. Kompaniets, A. S. Kozhin, A. S. Ovechkin, A. A. Petrukhin, V. V. Shutenko, and I. I. Yashin. "The registration system of the coordinate-tracking setup on the drift chambers." Journal of Physics: Conference Series 675, no. 3 (February 5, 2016): 032039. http://dx.doi.org/10.1088/1742-6596/675/3/032039.

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Fryskowska, A. "ACCURACY ASSESSMENT OF POINT CLOUDS GEO-REFERENCING IN SURVEYING AND DOCUMENTATION OF HISTORICAL COMPLEXES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5/W1 (May 15, 2017): 161–65. http://dx.doi.org/10.5194/isprs-archives-xlii-5-w1-161-2017.

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Terrestrial Laser Scanning (TLS) technique is widely used for documentation and preservation of historical sites by for example creating three-dimensional (3-D) digital models or vectorial sketches. In consequence, a complex, complete, detail and accurate documentation of historical structure is created. It is very crucial when it comes about modern digital culture. <br><br> If we acquire TLS data of once particular structure usually we do it in local coordinate system of scanner. Nevertheless when measurements are conducted for complex of several historical buildings or monuments (i.e. castle ruins, building of narrow streets of the Old Towns), the registration of point clouds into a common, global coordinate system is one of the critical steps in TLS data processing. Then we have integrate data with different accuracy level. Inner accuracy of local coordinate system (scanner system) is usually thrice higher than for global coordinate systems measurement. <br><br> The paper describes the geometric quality of the direct georeferencing in post-processing, considering surveying points. Then, an analysis of factors affecting registration accuracy is proposed. Finally, an improvement of direct georeferencing technique is presented and examined. Furthermore, registered data and chosen orientation methods have been compared to each other.

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Kong, Xiangxiong. "Identifying Geomorphological Changes of Coastal Cliffs through Point Cloud Registration from UAV Images." Remote Sensing 13, no. 16 (August 9, 2021): 3152. http://dx.doi.org/10.3390/rs13163152.

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Cliff monitoring is essential to stakeholders for their decision-making in maintaining a healthy coastal environment. Recently, photogrammetry-based technology has shown great successes in cliff monitoring. However, many methods to date require georeferencing efforts by either measuring geographic coordinates of the ground control points (GCPs) or using global navigation satellite system (GNSS)-enabled unmanned aerial vehicles (UAVs), significantly increasing the implementation costs. In this study, we proposed an alternative cliff monitoring methodology that does not rely on any georeferencing efforts but can still yield reliable monitoring results. To this end, we treated 3D point clouds of the cliff from different periods as geometric datasets and further aligned them into the same coordinate system using a rigid registration protocol. We examined the performance of our approach through a few small-scale experiments on a rock sample as well as a full-scale field validation on a coastal cliff. The findings of this study would be particularly valuable for underserved coastal communities, where high-end GPS devices and GIS specialists may not be easily accessible resources.

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Wu, Lu-shen, Guo-lin Wang, and Yun Hu. "Iterative closest point registration for fast point feature histogram features of a volume density optimization algorithm." Measurement and Control 53, no. 1-2 (January 2020): 29–39. http://dx.doi.org/10.1177/0020294019878869.

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Motivated by the high speed but insufficient precision of the existing fast point feature histogram algorithm, a new fast point feature histogram registration algorithm based on density optimization is proposed. In this method, a 44-section blank feature histogram is first established, and then a principal component analysis is implemented to calculate the normal of each point in the point cloud. By translating the coordinate system in the established local coordinate system, the normal angle of each point pair and its weighted neighborhood are obtained, and then a fast point feature histogram with 33 sections is established. The reciprocal of the volume density for the central point and its weighted neighborhood are calculated simultaneously. The whole reciprocal space is divided into 11 sections. Thus, a density fast point feature histogram with 44 sections is obtained. On inputting the testing models, the initial pose of the point cloud is adjusted using the traditional fast point feature histogram and the proposed algorithms, respectively. Then, the iterative closest point algorithm is incorporated to complete the fine registration test. Compared with the traditional fine registration test algorithm, the proposed optimization algorithm can obtain 44 feature parameters under the condition of a constant time complexity. Moreover, the proposed optimization algorithm can reduce the standard deviation by 8.6% after registration. This demonstrates that the proposed method encapsulates abundant information and can achieve a high registration accuracy.

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Wang, Hong Ke, and Xiao Feng Wang. "3D Registration Based on Planar Feature Segmentation and Plane Fit." Applied Mechanics and Materials 233 (November 2012): 274–77. http://dx.doi.org/10.4028/www.scientific.net/amm.233.274.

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3D reconstruction is used in applications such as virtual reality, digital cinematography and urban planning .The 3D registration is the important part of 3D reconstruction, which is one of outstanding and very basic problems in computer vision. In the paper, considering that there often exist a great number of planes in scenes, we show a planar-feature-based registration method. The planar features from the range image are extracted. Then, we can compute the transformation by SVD between the two coordinate systems and achieve the registration of these two range images.

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Mora, Rocio, Jose Antonio Martín-Jiménez, Susana Lagüela, and Diego González-Aguilera. "Automatic Point-Cloud Registration for Quality Control in Building Works." Applied Sciences 11, no. 4 (February 5, 2021): 1465. http://dx.doi.org/10.3390/app11041465.

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Total and automatic digitalization of indoor spaces in 3D implies a great advance in building maintenance and construction tasks, which currently require visits and manual works. Terrestrial laser scanners (TLS) have been widely used for these tasks, although the acquisition methodology with TLS systems is time consuming, and each point cloud is acquired in a different coordinate system, so the user has to post-process the data to clean and get a unique point cloud of the whole scenario. This paper presents a solution for the automatic data acquisition and registration of point clouds from indoor scenes, designed for point clouds acquired with a terrestrial laser scanner (TLS) mounted on an unmanned ground vehicle (UGV). The methodology developed allows the generation of one complete dense 3D point cloud consisting of the acquired point clouds registered in the same coordinate system, reaching an accuracy below 1 cm in section dimensions and below 1.5 cm in walls thickness, which makes it valid for quality control in building works. Two different study cases corresponding to building works were chosen for the validation of the method, showing the applicability of the methodology developed for tasks related to the control of the evolution of the construction.

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Yang, Hou Jun, Wei Zhong Zhang, and Xiao Lie Liu. "Rapid Method for Point Clouds Registration Based on Reference Points." Applied Mechanics and Materials 48-49 (February 2011): 873–76. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.873.

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Incremental point clouds registration is studied in this paper. A rapid method for point clouds registration based on reference points is proposed, which consists of the coarse registration and fine registration. Firstly, a set of reference points is applied as an assistant utility to measure the object. The transformation parameters are estimated by using the reference points only for coarse registration, and then dense point clouds data will be transformed to the same coordinate system. Secondly, taking the coarse registration results as the initial value, the improved Interactive Closest Point (ICP) algorithm is used in fine registration the original corresponding points are established rapidly by using the k-d tree searching algorithm. Finally, Preview Model Parameters Evaluation Random Sample Consensus (PERANSAC) algorithm is utilized to remove outliers. The experimental result shows that this method in finding original corresponding points can greatly improve the computation efficiency and also improve the registration accuracy.

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Ruchti, Alexander, Alexander Neuwirth, Allison K. Lowman, Savannah R. Duenweg, Peter S. LaViolette, and John D. Bukowy. "Homologous point transformer for multi-modality prostate image registration." PeerJ Computer Science 8 (December 1, 2022): e1155. http://dx.doi.org/10.7717/peerj-cs.1155.

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Registration is the process of transforming images so they are aligned in the same coordinate space. In the medical field, image registration is often used to align multi-modal or multi-parametric images of the same organ. A uniquely challenging subset of medical image registration is cross-modality registration—the task of aligning images captured with different scanning methodologies. In this study, we present a transformer-based deep learning pipeline for performing cross-modality, radiology-pathology image registration for human prostate samples. While existing solutions for multi-modality prostate image registration focus on the prediction of transform parameters, our pipeline predicts a set of homologous points on the two image modalities. The homologous point registration pipeline achieves better average control point deviation than the current state-of-the-art automatic registration pipeline. It reaches this accuracy without requiring masked MR images which may enable this approach to achieve similar results in other organ systems and for partial tissue samples.

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Chan, Ting On, Linyuan Xia, Derek D. Lichti, Xuanqi Wang, Xiong Peng, Yuezhen Cai, and Ming Ho Li. "A Method for Turning a Single Low-Cost Cube into a Reference Target for Point Cloud Registration." Applied Sciences 13, no. 3 (January 18, 2023): 1306. http://dx.doi.org/10.3390/app13031306.

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Target-based point cloud registration methods are still widely used by many laser scanning professionals due to their direct and manipulable nature. However, placing and moving multiple targets such as spheres for registration is a time-consuming and tactical process. When the number of scans gets large, the time and labor costs will accumulate to a high level. In this paper, we propose a flexible registration method that requires the installation of only a low-cost cubical target: a die-like object. The method includes virtual coordinate system construction and two error compensation techniques, in which the non-orthogonality of the scanned facets, along with the unknown sizes of the dice are estimated based on projection geometry and cubical constraints so that three pairs of conjugate points can be accurately identified along the axes of the constructed coordinate systems for the registration. No scan overlap of the facet is needed. Two different low-cost dice (with a volume of 0.125 m3 and 0.027 m3) were used for verifying the proposed method, which shows that the proposed method delivers registration accuracy (with an RMSE discrepancy of less than 0.5 mm for check planes) comparable to the traditional sphere- based method using four to six spherical targets spanning the scene. Therefore, the proposed method is particularly useful for registering point clouds in harsh scanning environments with limited target-setting space and high chances of target interruption.

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Hong, Sung-Eon. "A Study on the Unified Method of Coordinate Registration in Cadastral Map Information." Journal of the Korea Academia-Industrial cooperation Society 16, no. 11 (November 30, 2015): 7855–62. http://dx.doi.org/10.5762/kais.2015.16.11.7855.

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Zadeba, E. A., N. V. Ampilogov, N. S. Barbashina, A. G. Bogdanov, A. A. Borisov, N. S. Volkov, V. S. Vorobyev, et al. "Registration of muon bundles by a coordinate tracking unit based on drift chambers." Bulletin of the Russian Academy of Sciences: Physics 81, no. 4 (April 2017): 481–83. http://dx.doi.org/10.3103/s1062873817040414.

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Rajendra, Y. D., S. C. Mehrotra, K. V. Kale, R. R. Manza, R. K. Dhumal, A. D. Nagne, and A. D. Vibhute. "Evaluation of Partially Overlapping 3D Point Cloud's Registration by using ICP variant and CloudCompare." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 891–97. http://dx.doi.org/10.5194/isprsarchives-xl-8-891-2014.

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Terrestrial Laser Scanners (TLS) are used to get dense point samples of large object’s surface. TLS is new and efficient method to digitize large object or scene. The collected point samples come into different formats and coordinates. Different scans are required to scan large object such as heritage site. Point cloud registration is considered as important task to bring different scans into whole 3D model in one coordinate system. Point clouds can be registered by using one of the three ways or combination of them, Target based, feature extraction, point cloud based. For the present study we have gone through Point Cloud Based registration approach. We have collected partially overlapped 3D Point Cloud data of Department of Computer Science & IT (DCSIT) building located in Dr. Babasaheb Ambedkar Marathwada University, Aurangabad. To get the complete point cloud information of the building we have taken 12 scans, 4 scans for exterior and 8 scans for interior façade data collection. There are various algorithms available in literature, but Iterative Closest Point (ICP) is most dominant algorithms. The various researchers have developed variants of ICP for better registration process. The ICP point cloud registration algorithm is based on the search of pairs of nearest points in a two adjacent scans and calculates the transformation parameters between them, it provides advantage that no artificial target is required for registration process. We studied and implemented three variants Brute Force, KDTree, Partial Matching of ICP algorithm in MATLAB. The result shows that the implemented version of ICP algorithm with its variants gives better result with speed and accuracy of registration as compared with CloudCompare Open Source software.

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Journal articles on the topic 'Coordinate registration'

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